Certification Camps



Microsoft SQL 2016 Business Intelligence DevelopmentBootcamp Title – MCSA: SQL 2016 Business Intelligence Development (1 Cert) Number of Days – 6Number of Exams – 2Number of Certifications – 1Cost - $4,995.00Certifications:MCSA: SQL 2016 Business Intelligence DevelopmentExams:70-767:?Implementing a SQL Data Warehouse70-768:??Developing SQL Data ModelsCourse Description:The MCSA SQL 2016 Business Intelligence Development certification boot camp is a 6-day comprehensive deep dive into the SQL Server covering topics such as planning, monitoring, and configuring. This instructor led face to face training camp will teach you the skills needed to support a SQL Server environment.Course OutlineModule 1: Introduction to Data WarehousingDescribe data warehouse concepts and architecture considerations.LessonsOverview of Data WarehousingConsiderations for a Data Warehouse SolutionLab : Exploring a Data Warehouse SolutionAfter completing this module, you will be able to:Describe the key elements of a data warehousing solutionDescribe the key considerations for a data warehousing solutionModule 2: Planning Data Warehouse InfrastructureThis module describes the main hardware considerations for building a data warehouse.LessonsConsiderations for Building a Data WarehouseData Warehouse Reference Architectures and AppliancesLab : Planning Data Warehouse InfrastructureAfter completing this module, you will be able to:Describe the main hardware considerations for building a data warehouseExplain how to use reference architectures and data warehouse appliances to create a data warehouseModule 3: Designing and Implementing a Data WarehouseThis module describes how you go about designing and implementing a schema for a data warehouse.LessonsLogical Design for a Data WarehousePhysical Design for a Data WarehouseLab : Implementing a Data Warehouse SchemaAfter completing this module, you will be able to:Implement a logical design for a data warehouseImplement a physical design for a data warehouseModule 4: Columnstore IndexesThis module introduces Columnstore Indexes.LessonsIntroduction to Columnstore IndexesCreating Columnstore IndexesWorking with Columnstore IndexesLab : Using Columnstore IndexesAfter completing this module, you will be able to:Create Columnstore indexesWork with Columnstore IndexesModule 5: Implementing an Azure SQL Data WarehouseThis module describes Azure SQL Data Warehouses and how to implement them.LessonsAdvantages of Azure SQL Data WarehouseImplementing an Azure SQL Data WarehouseDeveloping an Azure SQL Data WarehouseMigrating to an Azure SQ Data WarehouseLab : Implementing an Azure SQL Data WarehouseAfter completing this module, you will be able to:Describe the advantages of Azure SQL Data WarehouseImplement an Azure SQL Data WarehouseDescribe the considerations for developing an Azure SQL Data WarehousePlan for migrating to Azure SQL Data WarehouseModule 6: Creating an ETL SolutionAt the end of this module you will be able to implement data flow in a SSIS package.LessonsIntroduction to ETL with SSISExploring Source DataImplementing Data FlowLab : Implementing Data Flow in an SSIS PackageAfter completing this module, you will be able to:Describe ETL with SSISExplore Source DataImplement a Data FlowModule 7: Implementing Control Flow in an SSIS PackageThis module describes implementing control flow in an SSIS package.LessonsIntroduction to Control FlowCreating Dynamic PackagesUsing ContainersLab : Implementing Control Flow in an SSIS PackageLab : Using Transactions and CheckpointsAfter completing this module, you will be able to:Describe control flowCreate dynamic packagesUse containersModule 8: Debugging and Troubleshooting SSIS PackagesThis module describes how to debug and troubleshoot SSIS packages.LessonsDebugging an SSIS PackageLogging SSIS Package EventsHandling Errors in an SSIS PackageLab : Debugging and Troubleshooting an SSIS PackageAfter completing this module, you will be able to:Debug an SSIS packageLog SSIS package eventsHandle errors in an SSIS packageModule 9: Implementing an Incremental ETL ProcessThis module describes how to implement an SSIS solution that supports incremental DW loads and changing data.LessonsIntroduction to Incremental ETLExtracting Modified DataTemporal TablesLab : Extracting Modified DataLab : Loading Incremental ChangesAfter completing this module, you will be able to:Describe incremental ETLExtract modified dataDescribe temporal tablesModule 10: Enforcing Data QualityThis module describes how to implement data cleansing by using Microsoft Data Quality services.LessonsIntroduction to Data QualityUsing Data Quality Services to Cleanse DataUsing Data Quality Services to Match DataLab : Cleansing DataLab : De-duplicating DataAfter completing this module, you will be able to:Describe data quality servicesCleanse data using data quality servicesMatch data using data quality servicesDe-duplicate data using data quality servicesModule 11: Using Master Data ServicesThis module describes how to implement master data services to enforce data integrity at source.LessonsMaster Data Services ConceptsImplementing a Master Data Services ModelManaging Master DataCreating a Master Data HubLab : Implementing Master Data ServicesAfter completing this module, you will be able to:Describe the key concepts of master data servicesImplement a master data service modelManage master dataCreate a master data hubModule 12: Extending SQL Server Integration Services (SSIS)This module describes how to extend SSIS with custom scripts and components.LessonsUsing Custom Components in SSISUsing Scripting in SSISLab : Using Scripts and Custom ComponentsAfter completing this module, you will be able to:Use custom components in SSISUse scripting in SSISModule 13: Deploying and Configuring SSIS PackagesThis module describes how to deploy and configure SSIS packages.LessonsOverview of SSIS DeploymentDeploying SSIS ProjectsPlanning SSIS Package ExecutionLab : Deploying and Configuring SSIS PackagesAfter completing this module, you will be able to:Describe an SSIS deploymentDeploy an SSIS packagePlan SSIS package executionModule 14: Consuming Data in a Data WarehouseThis module describes how to debug and troubleshoot SSIS packages.LessonsIntroduction to Business IntelligenceIntroduction to ReportingAn Introduction to Data AnalysisAnalyzing Data with Azure SQL Data WarehouseLab : Using Business Intelligence ToolsAfter completing this module, you will be able to:Describe at a high level business intelligenceShow an understanding of reportingShow an understanding of data analysisAnalyze data with Azure SQL data warehouseCourse OutlineModule 1: Introduction to Business Intelligence and Data ModelingThis module introduces key BI concepts and the Microsoft BI product suite.LessonsIntroduction to Business IntelligenceThe Microsoft business intelligence platformLab : Exploring a Data WarehouseAfter completing this module, you will be able to:Describe the concept of business intelligenceDescribe the Microsoft business intelligence platformModule 2: Creating Multidimensional DatabasesThis module describes the steps required to create a multidimensional database with analysis services.LessonsIntroduction to multidimensional analysisCreating data sources and data source viewsCreating a cubeOverview of cube securityLab : Creating a multidimensional databaseAfter completing this module, you will be able to:Use multidimensional analysisCreate data sources and data source viewsCreate a cubeDescribe cube securityModule 3: Working with Cubes and DimensionsThis module describes how to implement dimensions in a cube.LessonsConfiguring dimensionsDefine attribute hierarchiesSorting and grouping attributesLab : Working with Cubes and DimensionsAfter completing this module, you will be able to:Configure dimensionsDefine attribute hierarchies.Sort and group attributesModule 4: Working with Measures and Measure GroupsThis module describes how to implement measures and measure groups in a cube.LessonsWorking with measuresWorking with measure groupsLab : Configuring Measures and Measure GroupsAfter completing this module, you will be able to:Work with measuresWork with measure groupsModule 5: Introduction to MDXThis module describes the MDX syntax and how to use MDX.LessonsMDX fundamentalsAdding calculations to a cubeUsing MDX to query a cubeLab : Using MDXAfter completing this module, you will be able to:Describe the fundamentals of MDXAdd calculations to a cubeQuery a cube using MDXModule 6: Customizing Cube FunctionalityThis module describes how to customize a cube.LessonsImplementing key performance indicatorsImplementing actionsImplementing perspectivesImplementing translationsLab : Customizing a CubeAfter completing this module, you will be able to:Implement key performance indicatorsImplement actionsImplement perspectivesImplement translationsModule 7: Implementing a Tabular Data Model by Using Analysis ServicesThis module describes how to implement a tabular data model in PowerPivot.LessonsIntroduction to tabular data modelsCreating a tabular data modelUsing an analysis services tabular model in an enterprise BI solutionLab : Working with an Analysis services tabular data modelAfter completing this module, you will be able to:Describe tabular data modelsCreate a tabular data modelBe able to use an analysis services tabular data model in an enterprise BI solutionModule 8: Introduction to Data Analysis Expression (DAX)This module describes how to use DAX to create measures and calculated columns in a tabular data model.LessonsDAX fundamentalsUsing DAX to create calculated columns and measures in a tabular data modelLab : Creating Calculated Columns and Measures by using DAXAfter completing this module, you will be able to:Describe the fundamentals of DAXUse DAX to create calculated columns and measures in a tabular data modelModule 9: Performing Predictive Analysis with Data MiningThis module describes how to use data mining for predictive analysis.LessonsOverview of data miningUsing the data mining add-in for ExcelCreating a custom data mining solutionValidating a data mining modelConnecting to and consuming a data mining modelLab : Perform Predictive Analysis with Data MiningAfter completing this module, you will be able to:Describe data miningUse the data mining add-in for ExcelCreate a custom data mining solutionValidate a data mining solutionConnect to and consume a data mining solution ................
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